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Storing Data: Disks and Files

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Storing Data: Disks and Files. Lecture 3 (R&G Chapter 9). “Yea, from the table of my memory I’ll wipe away all trivial fond records.” -- Shakespeare, Hamlet. Review. Aren’t Databases Great? Relational model SQL. Query Optimization and Execution. Relational Operators. - PowerPoint PPT Presentation
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Storing Data: Disks and Files Lecture 3 (R&G Chapter 9) “Yea, from the table of my memory wipe away all trivial fond records.” -- Shakespeare, Hamlet
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Page 1: Storing Data:  Disks and Files

Storing Data: Disks and Files Lecture 3

(R&G Chapter 9)

“Yea, from the table of my memoryI’ll wipe away all trivial fond records.”

-- Shakespeare, Hamlet

Page 2: Storing Data:  Disks and Files

Review• Aren’t Databases Great?

• Relational model• SQL

Page 3: Storing Data:  Disks and Files

Disks, Memory, and Files

Query Optimizationand Execution

Relational Operators

Files and Access Methods

Buffer Management

Disk Space Management

DB

The BIG picture…

Page 4: Storing Data:  Disks and Files

Disks and Files • DBMS stores information on disks.

– In an electronic world, disks are a mechanical anachronism!

• This has major implications for DBMS design!– READ: transfer data from disk to main memory

(RAM).– WRITE: transfer data from RAM to disk.– Both are high-cost operations, relative to in-

memory operations, so must be planned carefully!

Page 5: Storing Data:  Disks and Files

Why Not Store Everything in Main Memory?

• Costs too much. For $1000, Dell will sell you either 2 GB of RAM or 180 GB of disk today.

• Main memory is volatile. We want data to be saved between runs. (Obviously!)

• Typical storage hierarchy:– Main memory (RAM) for currently used data.– Disk for the main database (secondary storage).– Tapes for archiving older versions of the data

(tertiary storage)

Page 6: Storing Data:  Disks and Files

Disks• Secondary storage device of choice. • Main advantage over tapes: random

access vs. sequential.• Data is stored and retrieved in units

called disk blocks or pages.• Unlike RAM, time to retrieve a disk block

varies depending upon location on disk. – Therefore, relative placement of blocks on

disk has major impact on DBMS performance!

Page 7: Storing Data:  Disks and Files

Components of a Disk

Platters

The platters spin (say, 120 rps).

Spindle

The arm assembly is moved in or out to position a head on a desired track. Tracks under heads make a cylinder (imaginary!).

Disk head

Arm movement

Arm assembly

Only one head reads/writes at any one time.

Tracks

Sector

Block size is a multiple of sector size (which is fixed).

Page 8: Storing Data:  Disks and Files

Accessing a Disk Page• Time to access (read/write) a disk block:

– seek time (moving arms to position disk head on track)– rotational delay (waiting for block to rotate under head)– transfer time (actually moving data to/from disk surface)

• Seek time and rotational delay dominate.– Seek time varies between about 0.3 and 10msec– Rotational delay varies from 0 to 6msec– Transfer rate around .008msec per 8K block

• Key to lower I/O cost: reduce seek/rotation delays! Hardware vs. software solutions?

Page 9: Storing Data:  Disks and Files

Arranging Pages on Disk• `Next’ block concept:

– blocks on same track, followed by– blocks on same cylinder, followed by– blocks on adjacent cylinder

• Blocks in a file should be arranged sequentially on disk (by `next’), to minimize seek and rotational delay.

• For a sequential scan, pre-fetching several pages at a time is a big win!

Page 10: Storing Data:  Disks and Files

Disk Space Management• Lowest layer of DBMS software manages space on

disk (using OS file system or not?).• Higher levels call upon this layer to:

– allocate/de-allocate a page– read/write a page

• Best if a request for a sequence of pages is satisfied by pages stored sequentially on disk!– Responsibility of disk space manager.– Higher levels don’t know how this is done, or how free

space is managed.– Though they may assume sequential access for files!

• Hence disk space manager should do a decent job.

Page 11: Storing Data:  Disks and Files

Context

Query Optimizationand Execution

Relational Operators

Files and Access Methods

Buffer Management

Disk Space Management

DB

Page 12: Storing Data:  Disks and Files

Buffer Management in a DBMS

• Data must be in RAM for DBMS to operate on it!• Buffer Mgr hides the fact that not all data is in RAM

DB

MAIN MEMORY

DISK

disk page

free frame

Page Requests from Higher Levels

BUFFER POOL

choice of frame dictatedby replacement policy

Page 13: Storing Data:  Disks and Files

When a Page is Requested ...• Buffer pool information table contains:

<frame#, pageid, pin_count, dirty> • If requested page is not in pool:

– Choose a frame for replacement.Only “un-pinned” pages are candidates!

– If frame is “dirty”, write it to disk– Read requested page into chosen frame

• Pin the page and return its address.

If requests can be predicted (e.g., sequential scans) pages can be pre-fetched several pages at a time!

Page 14: Storing Data:  Disks and Files

More on Buffer Management• Requestor of page must eventually unpin it, and

indicate whether page has been modified: – dirty bit is used for this.

• Page in pool may be requested many times, – a pin count is used. – To pin a page, pin_count++– A page is a candidate for replacement iff pin count

== 0 (“unpinned”)• CC & recovery may entail additional I/O when a

frame is chosen for replacement. – Write-Ahead Log protocol; more later!

Page 15: Storing Data:  Disks and Files

Buffer Replacement Policy• Frame is chosen for replacement by a

replacement policy:– Least-recently-used (LRU), MRU, Clock, etc.

• Policy can have big impact on # of I/O’s; depends on the access pattern.

Page 16: Storing Data:  Disks and Files

LRU Replacement Policy• Least Recently Used (LRU)

– for each page in buffer pool, keep track of time when last unpinned

– replace the frame which has the oldest (earliest) time

– very common policy: intuitive and simple• Works well for repeated accesses to popular pages

• Problems?• Problem: Sequential flooding

– LRU + repeated sequential scans.– # buffer frames < # pages in file means each page

request causes an I/O. – Idea: MRU better in this scenario? We’ll see in HW1!

Page 17: Storing Data:  Disks and Files

“Clock” Replacement Policy• An approximation of LRU• Arrange frames into a cycle, store one

reference bit per frame– Can think of this as the 2nd chance bit

• When pin count reduces to 0, turn on ref. bit

• When replacement necessarydo for each page in cycle {

if (pincount == 0 && ref bit is on)turn off ref bit;

else if (pincount == 0 && ref bit is off)choose this page for replacement;

} until a page is chosen;Questions:How like LRU?Problems?

A(1)

B(p)

C(1)

D(1)

Page 18: Storing Data:  Disks and Files

DBMS vs. OS File System OS does disk space & buffer mgmt: why not let

OS manage these tasks?

• Some limitations, e.g., files can’t span disks.• Buffer management in DBMS requires ability to:

– pin a page in buffer pool, force a page to disk & order writes (important for implementing CC & recovery)

– adjust replacement policy, and pre-fetch pages based on access patterns in typical DB operations.

Page 19: Storing Data:  Disks and Files

Context

Query Optimizationand Execution

Relational Operators

Files and Access Methods

Buffer Management

Disk Space Management

DB

Page 20: Storing Data:  Disks and Files

Files of Records• Blocks interface for I/O, but…• Higher levels of DBMS operate on records,

and files of records.• FILE: A collection of pages, each containing

a collection of records. Must support:– insert/delete/modify record– fetch a particular record (specified using

record id)– scan all records (possibly with some

conditions on the records to be retrieved)

Page 21: Storing Data:  Disks and Files

Unordered (Heap) Files• Simplest file structure contains records in no

particular order.• As file grows and shrinks, disk pages are allocated and

de-allocated.• To support record level operations, we must:

– keep track of the pages in a file– keep track of free space on pages– keep track of the records on a page

• There are many alternatives for keeping track of this.– We’ll consider 2

Page 22: Storing Data:  Disks and Files

Heap File Implemented as a List

• The header page id and Heap file name must be stored someplace.– Database “catalog”

• Each page contains 2 `pointers’ plus data.

HeaderPage

DataPage

DataPage

DataPage

DataPage

DataPage

DataPage Pages with

Free Space

Full Pages

Page 23: Storing Data:  Disks and Files

Heap File Using a Page Directory

• The entry for a page can include the number of free bytes on the page.

• The directory is a collection of pages; linked list implementation is just one alternative.– Much smaller than linked list of all HF pages!

DataPage 1

DataPage 2

DataPage N

HeaderPage

DIRECTORY

Page 24: Storing Data:  Disks and Files

Indexes (a sneak preview)

• A Heap file allows us to retrieve records:– by specifying the rid, or– by scanning all records sequentially

• Sometimes, we want to retrieve records by specifying the values in one or more fields, e.g.,– Find all students in the “CS” department– Find all students with a gpa > 3

• Indexes are file structures that enable us to answer such value-based queries efficiently.

Page 25: Storing Data:  Disks and Files

Record Formats: Fixed Length

• Information about field types same for all records in a file; stored in system catalogs.

• Finding i’th field done via arithmetic.

Base address (B)

L1 L2 L3 L4

F1 F2 F3 F4

Address = B+L1+L2

Page 26: Storing Data:  Disks and Files

Record Formats: Variable Length• Two alternative formats (# fields is fixed):

Second offers direct access to i’th field, efficient storage of nulls (special don’t know value); small directory overhead.

$ $ $ $Fields Delimited by Special Symbols

F1 F2 F3 F4

F1 F2 F3 F4

Array of Field Offsets

Page 27: Storing Data:  Disks and Files

Page Formats: Fixed Length Records

Record id = <page id, slot #>. In first alternative, moving records for free space management changes rid; may not be acceptable.

Slot 1Slot 2

Slot N. . . . . .

N M10. . .M ... 3 2 1

PACKED UNPACKED, BITMAP

Slot 1Slot 2

Slot N

FreeSpace

Slot M11

number of records

numberof slots

Page 28: Storing Data:  Disks and Files

Page Formats: Variable Length Records

Can move records on page without changing rid; so, attractive for fixed-length records too.

Page iRid = (i,N)

Rid = (i,2)Rid = (i,1)

Pointerto startof freespace

SLOT DIRECTORY

N . . . 2 120 16 24 N

# slots

Page 29: Storing Data:  Disks and Files

System Catalogs• For each relation:

– name, file location, file structure (e.g., Heap file)– attribute name and type, for each attribute– index name, for each index– integrity constraints

• For each index:– structure (e.g., B+ tree) and search key fields

• For each view:– view name and definition

• Plus statistics, authorization, buffer pool size, etc.

Catalogs are themselves stored as relations!

Page 30: Storing Data:  Disks and Files

Attr_Cat(attr_name, rel_name, type, position)

attr_name rel_name type positionattr_name Attribute_Cat string 1rel_name Attribute_Cat string 2type Attribute_Cat string 3position Attribute_Cat integer 4sid Students string 1name Students string 2login Students string 3age Students integer 4gpa Students real 5fid Faculty string 1fname Faculty string 2sal Faculty real 3

Page 31: Storing Data:  Disks and Files

Summary• Disks provide cheap, non-volatile storage.

– Random access, but cost depends on location of page on disk; important to arrange data sequentially to minimize seek and rotation delays.

• Buffer manager brings pages into RAM.– Page stays in RAM until released by requestor.– Written to disk when frame chosen for replacement

(which is sometime after requestor releases the page).– Choice of frame to replace based on replacement

policy.– Tries to pre-fetch several pages at a time.

Page 32: Storing Data:  Disks and Files

Summary (Contd.)• DBMS vs. OS File Support

– DBMS needs features not found in many OS’s, e.g., forcing a page to disk, controlling the order of page writes to disk, files spanning disks, ability to control pre-fetching and page replacement policy based on predictable access patterns, etc.

• Variable length record format with field offset directory offers support for direct access to i’th field and null values.

• Slotted page format supports variable length records and allows records to move on page.

Page 33: Storing Data:  Disks and Files

Summary (Contd.)• File layer keeps track of pages in a file, and

supports abstraction of a collection of records.– Pages with free space identified using linked list or

directory structure (similar to how pages in file are kept track of).

• Indexes support efficient retrieval of records based on the values in some fields.

• Catalog relations store information about relations, indexes and views. (Information that is common to all records in a given collection.)


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